The dqrng package provides several fast random number generators together with fast functions for generating random numbers according to a uniform, normal and exponential distribution. These functions are modeled after the base functions set.seed, RNGkind, runif, rnorm, and rexp.

dqRNGkind(kind, normal_kind = "ignored")

dqrunif(n, min = 0, max = 1)

dqrnorm(n, mean = 0, sd = 1)

dqrexp(n, rate = 1)

dqset.seed(seed, stream = NULL)

Arguments

kind

string specifying the RNG (see details)

normal_kind

ignored; included for compatibility with RNGkind

n

number of observations

min

lower limit of the uniform distribution

max

upper limit of the uniform distribution

mean

mean value of the normal distribution

sd

standard deviation of the normal distribution

rate

rate of the exponential distribution

seed

integer scalar to seed the random number generator, or an integer vector of length 2 representing a 64-bit seed. Maybe NULL, see details.

stream

integer used for selecting the RNG stream; either a scalar or a vector of length 2

Value

dqrunif, dqrnorm, and dqrexp return a numeric vector of length n.

Details

Supported RNG kinds:

pcg64

The default 64 bit variant from the PCG family developed by Melissa O'Neill. See https://www.pcg-random.org/ for more details.

Xoroshiro128+ and Xoshiro256+

RNGs developed by David Blackman and Sebastiano Vigna. They are used as default RNGs in Erlang and Lua. See https://xoshiro.di.unimi.it/ for more details.

Threefry

The 64 bit version of the 20 rounds Threefry engine as provided by sitmo-package

Xoroshiro128+ is the default since it is the fastest generator provided by this package.

The functions dqrnorm and dqrexp use the Ziggurat algorithm as provided by boost.random.

See generateSeedVectors for rapid generation of integer-vector seeds that provide 64 bits of entropy. These allow full exploration of the state space of the 64-bit RNGs provided in this package.

If the provided seed is NULL, a seed is genenrated from R's RNG without state alteration.

See also

Examples

library(dqrng) # Set custom RNG. dqRNGkind("Xoshiro256+") # Use an integer scalar to set a seed. dqset.seed(42) # Use integer scalars to set a seed and the stream. dqset.seed(42, 123) # Use an integer vector to set a seed. dqset.seed(c(31311L, 24123423L)) # Use an integer vector to set a seed and a scalar to select the stream. dqset.seed(c(31311L, 24123423L), 123) # Random sampling from distributions. dqrunif(5, min = 2, max = 10)
#> [1] 9.254756 2.169924 3.232695 8.859045 4.940842
dqrexp(5, rate = 4)
#> [1] 0.003025477 0.213876337 0.008051277 0.399246137 0.066848602
dqrnorm(5, mean = 5, sd = 3)
#> [1] 1.399092 7.411358 7.145729 2.308440 6.766659